Background - Clinical frailty syndrome is a common geriatric syndrome, which is characterized by physiological reserve decreases and increased vulnerability. The changes associated to ageing and frailties are associated to changes in gait characteristics and the basic functional capacities. Traditional clinical evaluation of Sit-to-Stand (Si-St) and Stand-to-Sit (St-Si) transition is based on visual observation of joint angle motion to describe alterations in coordination and movement pattern. The latest generation smartphones often include inertial sensors with subunits such as accelerometers and gyroscopes, which can detect acceleration.

 Objective - Firstly, to describe the variability of the accelerations, angular velocity, and displacement of the trunk during the Sit-to-Stand and Stand-to-Sit transitions in two groups of frail and physically active elderly persons, through instrumentation with the iPhone 4 smartphone. Secondly, we want to analyze the differences between the two study groups.

 Methods - A cross-sectional study that involved 30 subjects over 65 years, 14 frail and 16 fit subjects. The participants were classified with frail syndrome by the Fried criteria. Linear acceleration was measured along three orthogonal axes using the iPhone 4 accelerometer. Each subject performed up to three successive Si-St and St-Si postural transitions using a standard chair with armrest.

 Results - Significant differences were found between the two groups of frail and fit elderly persons in the accelerometry and angular displacement variables obtained in the kinematic readings of the trunk during both transitions.

 Conclusions - The inertial sensor fitted in the iPhone 4 is able to study and analyze the kinematics of the Si-St and St-Si transitions in frail and physically active elderly persons. The accelerometry values for the frail elderly are lower than for the physically active elderly, while variability in the readings for the frail elderly is also lower than for the control group.

Differences in trunk accelerometry between frail and nonfrail elderly persons in sit-to-stand and stand-to-sit transitions based on a mobile inertial sensor

The present study was performed to investigate the validity of a wireless earbud-type inertial measurement unit (Ear-IMU) sensor used to estimate head angle during four workouts. In addition, relationships between head angle obtained from the Ear-IMU sensor and the angles of other joints determined with a 3D motion analysis system were investigated. The study population consisted of 20 active volunteers. The Ear-IMU sensor measured the head angle, while a 3D motion analysis system simultaneously measured the angles of the head, trunk, pelvis, hips, and knees during workouts. Comparison with the head angle measured using the 3D motion analysis system indicated that the validity of the Ear-IMU sensor was very strong or moderate in the sagittal and frontal planes. In addition, the trunk angle in the frontal plane showed a fair correlation with the head angle determined with the Ear-IMU sensor during a single-leg squat, reverse lunge, and standing hip abduction; the correlation was poor in the sagittal plane. Our results indicated that the Ear-IMU sensor can be used to directly estimate head motion and indirectly estimate trunk motion.

/pdf/the-validity-of-wireless-earbud-type-wearable-sensors-for-2dh6dh13.pdf

The Validity of Wireless Earbud-Type Wearable Sensors for Head Angle Estimation and the Relationships of Head with Trunk, Pelvis, Hip, and Knee during Workouts

The study aims to determine the validity and reproducibility of step duration and step length parameters measured during walking in healthy participants using an accelerometer embedded in smart eyeglasses. Twenty young volunteers participated in two identical sessions comprising a 30 s gait assessment performed at three different treadmill speeds under two conditions (i.e., with and without a cervical collar). Spatiotemporal parameters (i.e., step duration and step length normalized by the lower limb length) were obtained with both the accelerometer embedded in smart eyeglasses and an optoelectronic system. The relative intra- and inter-session reliability of step duration and step length computed from the vertical acceleration data were excellent for all experimental conditions. An excellent absolute reliability was observed for the eyeglasses for all conditions and concurrent validity between systems was observed. An accelerometer incorporated in smart eyeglasses is accurate to measure step duration and step length during gait.

/pdf/smart-eyeglasses-a-valid-and-reliable-device-to-assess-3jpfenh7.pdf

Smart Eyeglasses: A Valid and Reliable Device to Assess Spatiotemporal Parameters during Gait

Validity of a simple sit-to-stand method for assessing force-velocity profile in older adults.

Monitoring and analyzing basic human daily life activities will help in enhancing the quality of life for both healthy and physically handicapped people. The recognition of sit-to-stand and stand-to-sit transitions in activities of daily living (ADL) is complex task. This is due to the intricate body’s movements during such postural transition. This work proposes a novel method for detecting sit-to-stand and stand-to-sit postural transitions in addition to other human physical activities such as walk and no-walk. In contrast to previous methods for such transitions determination, our solution does not require complex time- or frequency-domain based algorithms. Our solution relies on fusing motion data collected from an inertial measurement unit device with light data generated from visible light sensing technology utilizing an RGB photodiode. By utilizing a low-complex decision tree algorithm, the activity can be precisely recognized in resource-efficient way. The applicability of our approach was tested through two scenarios representing various ADL in smart environment.

Sit-to-stand and Stand-to-sit Activities Recognition by Visible Light Sensing

Wearable sensors have recently been used to evaluate biomechanical parameters of everyday movements, but few have been located at the head level. This study investigated the relative and absolute reliability (intra- and inter-session) and concurrent validity of an inertial measurement unit (IMU) embedded in smart eyeglasses during sit-to-stand (STS) movements for the measurement of maximal acceleration of the head. Reliability and concurrent validity were investigated in nineteen young and healthy participants by comparing the acceleration values of the glasses’ IMU to an optoelectronic system. Sit-to-stand movements were performed in laboratory conditions using standardized tests. Participants wore the smart glasses and completed two testing sessions with STS movements performed at two speeds (slow and comfortable) under two different conditions (with and without a cervical collar). Both the vertical and anteroposterior acceleration values were collected and analyzed. The use of the cervical collar did not significantly influence the results obtained. The relative reliability intra- and inter-session was good to excellent (i.e., intraclass correlation coefficients were between 0.78 and 0.91) and excellent absolute reliability (i.e., standard error of the measurement lower than 10% of the average test or retest value) was observed for the glasses, especially for the vertical axis. Whatever the testing sessions in all conditions, significant correlations (p < 0.001) were found for the acceleration values recorded either in the vertical axis and in the anteroposterior axis between the glasses and the optoelectronic system. Concurrent validity between the glasses and the optoelectronic system was observed. Our observations indicate that the IMU embedded in smart glasses is accurate to measure vertical acceleration during STS movements. Further studies should investigate the use of these smart glasses to assess the STS movement in unstandardized settings (i.e., clinical and/or home) and to report vertical acceleration values in an elderly population of fallers and non-fallers.

https://www.mdpi.com/1424-8220/20/18/5019/pdf

Sit-To-Stand Movement Evaluated Using an Inertial Measurement Unit Embedded in Smart Glasses—A Validation Study

Background As people age, their physical capacities (eg, walking and balance) decline and the risk of falling rises. Yet, classic fall detection devices are poorly accepted by older adults. Because they often wear eyeglasses as they go about their daily activities, daily monitoring to detect and prevent falls with smart eyeglasses might be more easily accepted. Objective On the basis of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), this study evaluated (1) the acceptability of smart eyeglasses for the detection and prevention of falls by older adults and (2) the associations with selected fall-related functional physical capacities. Methods A total of 142 volunteer older adults (mean age 74.9 years, SD 6.5 years) completed the UTAUT2 questionnaire adapted for smart eyeglasses and then performed several physical tests: a unipodal balance test with eyes open and closed, a 10-m walk test, and a 6-minute walk test. An unsupervised analysis classified the participants into physical performance groups. Multivariate ANOVAs were performed to identify differences in acceptability constructs according to the performance group. Results The UTAUT2 questionnaire adapted for eyeglasses presented good psychometric properties. Performance expectancy (β=.21, P=.005), social influence (β=.18, P=.007), facilitating conditions (β=.17, P=.04), and habit (β=.40, P<.001) were significant contributors to the behavioral intention to use smart eyeglasses (R²=0.73). The unsupervised analysis based on fall-related functional physical capacities created 3 groups of physical performance: low, intermediate, and high. Effort expectancy in the low performance group (mean 3.99, SD 1.46) was lower than that in the other 2 groups (ie, intermediate: mean 4.68, SD 1.23; high: mean 5.09, SD 1.41). Facilitating conditions in the high performance group (mean 5.39, SD 1.39) were higher than those in the other 2 groups (ie, low: mean 4.31, SD 1.68; intermediate: mean 4.66, SD 1.51). Conclusions To our knowledge, this study is the first to examine the acceptability of smart eyeglasses in the context of fall detection and prevention in older adults and to associate acceptability with fall-related functional physical capacities. The older adults with higher physical performances, and possibly lower risks of falling, reported greater acceptability of smart eyeglasses for fall prevention and detection than their counterparts exhibiting low physical performances.

Applying the UTAUT2 Model to Smart Eyeglasses to Detect and Prevent Falls Among Older Adults and Examination of Associations With Fall-Related Functional Physical Capacities: Survey Study

Justine Hellec

Papers

Sit-To-Stand Movement Evaluated Using an Inertial Measurement Unit Embedded in Smart Glasses—A Validation Study

Smart Eyeglasses: A Valid and Reliable Device to Assess Spatiotemporal Parameters during Gait

Applying the UTAUT2 Model to Smart Eyeglasses to Detect and Prevent Falls Among Older Adults and Examination of Associations With Fall-Related Functional Physical Capacities: Survey Study